EgoNet: identification of human disease ego-network modules.

ABSTRACT:

Background

Mining novel biomarkers from gene expression profiles for accurate disease classification is challenging due to small sample size and high noise in gene expression measurements. Several studies have proposed integrated analyses of microarray data and protein-protein interaction (PPI) networks to find diagnostic subnetwork markers. However, the neighborhood relationship among network member genes has not been fully considered by those methods, leaving many potential gene markers unidentified. The main idea of this study is to take full advantage of the biological observation that genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks.

Results

We present EgoNet, a novel method based on egocentric network-ana

SUBMITTER: Yang R 

PROVIDER: S-EPMC4234496 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature